Welcome to MindGraph, a proof of concept, open-source, API-first graph-based project designed for natural language interactions (input and output). This prototype serves as a template for building and customizing your own CRM solutions with a focus on ease of integration and extendibility.
Before you begin, ensure you have the following installed:
- Python 3.6 or higher
- Flask, which can be installed via pip:
pip install Flask
After cloning the repository, navigate to the root directory and start the Flask server with:
python main.py
The server will launch on http://0.0.0.0:81
.
MindGraph is organized into several key components:
main.py
: The entry point to the application.app/__init__.py
: Sets up the Flask app and integrates the blueprints.models.py
: Manages the in-memory graph data structure for entities and relationships.views.py
: Hosts the API route definitions.integration_manager.py
: Handles the dynamic registration and management of integration functions.signals.py
: Sets up signals for creating, updating, and deleting entities.
MindGraph employs a sophisticated integration system designed to extend the application's base functionality dynamically. At the core of this system is integration_manager.py
, which acts as a registry and executor for various integration functions. This modular architecture allows AutoPlex to incorporate AI-powered features seamlessly, such as processing natural language inputs into structured knowledge graphs through integrations like natural_input.py
. Further integrations, including add_multiple_conditional
, conditional_entity_addition
, and conditional_relationship_addition
, work in tandem to ensure the integrity and enhancement of the application's data model.
Entity Management: Entities are stored in an in-memory graph for quick access and manipulation, allowing CRUD operations on people, organizations, and their interrelations.
Integration Triggers: Custom integration functions can be triggered via HTTP requests, enabling the CRM to interact with external systems or run additional processing.
Search Capabilities: Entities and their relationships can be easily searched with custom query parameters.
AI Readiness: Designed with AI integrations in mind, facilitating the incorporation of intelligent data processing and decision-making.
MindGraph provides a series of RESTful endpoints:
POST /<entity_type>
: Create an entity.GET /<entity_type>/<int:entity_id>
: Retrieve an entity.GET /<entity_type>
: List all entities of a type.PUT /<entity_type>/<int:entity_id>
: Update an entity.DELETE /<entity_type>/<int:entity_id>
: Remove an entity.POST /relationship
: Establish a new relationship.GET /search/entities/<entity_type>
: Search for entities.GET /search/relationships
: Find relationships.
POST /trigger-integration/<integration_name>
: Activates a predefined integration function.
To incorporate a new integration into AutoPlex, create a Python module within the integrations
directory. This module should define the integration's logic and include a register
function that connects the integration to the IntegrationManager
. Ensure that your integration interacts properly with the application's components, such as models.py
for data operations and views.py
for activation via API endpoints. This approach allows AutoPlex to dynamically expand its capabilities through modular and reusable code.
Signals are emitted for entity lifecycle events, providing hooks for extending functionality or syncing with other systems.
To create a person via curl
:
curl -X POST http://0.0.0.0:81/people \
-H "Content-Type: application/json" \
-d '{"name":"Jane Doe","age":28}'
To demonstrate the power of MindGraph's integration system, here are some example commands:
curl -X POST http://0.0.0.0:81/trigger-integration/natural_input \
-H "Content-Type: application/json" \
-d '{"input":"Company XYZ organized an event attended by John Doe and Jane Smith."}'
Let's be honest... I don't maintain projects. If you want to take over/manage this, let me know (X/Twitter is a good channel). Otherwise, enjoy this proof of concept starter kit as it is :)
MindGraph is distributed under the MIT License. See LICENSE
for more information.
Just tag me on Twitter/X https://twitter.com/yoheinakajima
Project Link: https://github.com/yoheinakajima/MindGraph